Research On Energy Management For Fuel Cell Hybrid Tramway

With the acceleration of the urbanization process,the urban population has grown rapidly,and it has also exacerbated the problems of energy crisis and traffic congestion.To alleviate these problems,governments are calling on people to choose green and energy-efficient public transportation,and have invested a lot of money.In all types of public transportation,trams with better comfort and economy are favored by the government and the people.Hybrid trams,which use fuel cells as the main power source,do not need to set up a power grid,so they are safe and beautiful,and the costs are low.The research of fuel cell hybrid tramway has also been widely concerned by scholars.This dissertation takes the fuel-cell/supercapacitor/battery hybrid tram as the application background and takes the energy management strategy of the onboard hybrid power system as the main research object.The paper studies various types of energy management strategies and aimed at improving the economic performance of fuel cell hybrid trams.(1)The fuel cell hybrid tram model is introduced from the perspective of energy flow.Then,the energy management strategy based on the operation state is introduced,and for reducing the consumption of hydrogen fuel,the energy management strategy based on a genetic algorithm is introduced.These two strategies will be used as the benchmark strategy for subsequent research.(2)Considering the two goals of reducing fuel consumption and increasing the life of energy storage equipment,performance index evaluation models were established respectively.Aiming at the problem that two indexes are not easy to be evaluated in the same equation,a Pareto optimization method for fuel cell tram energy management strategy is proposed.On the one hand,the method combines the non-dominated sorting algorithm with the tram operation state strategy to obtain the Pareto optimal solution set of the energy management strategy.On the other hand,the method analyzes the effect of optimization parameters on the objective function and summarizes the laws.Finally,using the laws as the guide,a comprehensive optimal solution is selected from the optimal solution set.(3)Taking into account the factors such as hydrogen fuel cost,purchase cost,replacement cost,maintenance cost,and charging cost,a simplified model of the life-cycle cost of the fuel cell hybrid power system is established.Taking this model as the objective function,two heuristic algorithms: multiple-population genetic algorithm and artificial fish swarm algorithm are introduced into the fuel cell trams,and two global optimized energy management strategies are proposed.To obtain a better optimization result,the immigration operator and manual selection operator of the multiple-population genetic algorithm are extracted and combined with the firefly algorithm.Then,a fuel cell tram energy management strategy based on multiple-population firefly algorithm is proposed.(4)Apply the equivalent consumption minimum strategy to this scenario.As the traditional equivalent consumption minimization strategy cannot be directly applied to the fuel cell/supercapacitor/battery hybrid power system,a state machine controller was introduced.The improved equivalent consumption minimization strategies for power battery priority and supercapacitor priority versions are designed,and the lower cost supercapacitor priority version is used as the basic version.To get better global performance,some appropriate optimization variables are analyzed and selected.Then,an equivalent consumption minimization strategy based on the firefly algorithm is proposed.(5)The application effect of simultaneously optimizing the target speed curve and energy management strategies for fuel cell trams is studied.First,a method for optimizing the target speed curve of fuel cell trams is introduced,and it is verified that the method can improve the running cost of the vehicles.Then,the relationship between the target speed curve of the tram and the energy management strategy is analyzed,and the firefly algorithm and genetic algorithm are introduced to design three simultaneous optimization schemes for the speed curve and energy management: parallel scheme,sequential scheme,and collaborative scheme.For the collaborative optimization scheme,a hybrid intelligent algorithm based on the firefly algorithm and genetic algorithm is introduced.Based on the hybrid intelligent algorithm,the collaborative optimization plan includes two optimization processes: the outer layer uses the firefly algorithm to optimize the operating speed curve,and the optimization result is used as the input parameter of the inner layer.The inner layer uses the genetic algorithm to optimize the energy management strategy,and enter the optimal result into the outer layer to calculate the cost.